3D TOF MRA Research Articles

The value of multimodal imaging fusion in preoperative visualization assessment of neurovascular relationship in hemifacial spasm: a single-center retrospective study.

The neurovascular conflict (NVC) at the brainstem exit zone of the facial nerve is considered the primary etiology of primary hemifacial spasm (HFS). Therefore, microvascular decompression (MVD) has become the preferred treatment for HFS. Successful neurovascular decompression can achieve significant therapeutic effects, and accurately identifying the site of compression is crucial for the success of this surgery. Detailed diagnostic neuroimaging plays an important role in accurately identifying the site of compression.The purpose of this study is to explore the feasibility and predictive value of preoperative visualization assessment of the neurovascular relationship in HFS using 3D Slicer software based on multimodal imaging fusion. This aims to reduce the omission of responsible vessels and lower the incidence of postoperative complications, thereby potentially improving the efficacy and safety of the surgery. This study retrospectively analyzed 80 patients with HFS who underwent MVD surgery. All patients underwent preoperative cranial MRI scans, including the 3D-FIESTA and the 3D-TOF MRA sequences. Three-dimensional models were reconstructed from the multimodal MRI images using 3D Slicer software. Independent observers, who were blinded to the surgical outcomes, evaluated the neurovascular relationships using both the three-dimensional models and multimodal MRI images. The assessment results were compared with intraoperative findings, and statistical analysis was conducted using SPSS 22.0 software. The agreement between preoperative assessment using the 3D-TOF MRA sequence combined with the 3D-FIESTA sequence and intraoperative findings was represented by a Kappa value of 0.343, while the Kappa value for agreement between three-dimensional reconstruction and intraoperative findings was 0.637. There was a statistically significant difference between the two methods ( X2 = 18.852, P = 0.001 ). The sensitivity and specificity of the 3D-TOF MRA sequence combined with the 3D-FIESTA sequence for evaluating neurovascular relationships were 92.4% and 100%, respectively, while for three-dimensional reconstruction, both were 100%. The Kappa value for agreement between preoperative the 3D-TOF MRA sequence combined with the 3D-FIESTA sequence prediction of offending vessels and intraoperative findings was 0.625, while the Kappa value for agreement between three-dimensional reconstruction and intraoperative findings was 0.938, showing a statistically significant difference ( X2 = 317.798, P = 0.000 ). The Kappa value for agreement between preoperative the 3D-TOF MRA sequence combined with the 3D-FIESTA sequence assessment of the anatomical location of facial nerve involvement in neurovascular compression and intraoperative findings was 0.608, while the Kappa value for agreement between three-dimensional reconstruction and intraoperative findings was 0.918, also showing a statistically significant difference ( X2 = 504.647, P = 0.000 ). The preoperative visualization assessment of neurovascular relationships in HFS using 3D Slicer software based on multimodal imaging fusion has been demonstrated to be reliable. It is more accurate than combining the 3D-TOF MRA sequence with the 3D-FIESTA sequence and shows higher consistency with intraoperative findings. This method provides guidance for surgical procedures and thereby potentially enhances the efficacy and safety of surgeries to a certain extent.

Diagnostic Performance of TOF, 4D MRA, Arterial Spin-Labeling, and Susceptibility-Weighted Angiography Sequences in the Post-Radiosurgery Monitoring of Brain AVMs.

Brain AVMs are congenital anomalies of the cerebrovascular system, often discovered incidentally or through symptomatic presentations such as intracranial hemorrhage, seizure, headache, or neurologic deficits. Various treatment modalities exist for AVMs, including radiosurgery, a treatment technique that is noninvasive and efficient. Accurate imaging is crucial for risk assessment, treatment planning, and monitoring of these patients before and after radiosurgery. Currently, DSA is the preferred imaging technique. Despite its efficacy, DSA is notably invasive, presenting inherent risks to the patients. This systematic review and meta-analysis aimed to evaluate the efficacy of MRI sequences for monitoring brain AVMs after radiosurgery. We performed a comprehensive search of PubMed, Scopus, Web of Science, and EMBASE databases and a methodologic quality assessment with the QUADAS-2 checklist diagnostic test accuracy. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 3,220 abstracts were screened, 98 articles were reviewed in full text, and 14 articles met the inclusion criteria. We used the bivariate random-effects meta-analysis model with STATA/MP 17 software for data analysis. No publication bias was detected. Fourteen studies were eligible for qualitative and quantitative analysis. MRI offers high sensitivity (85%) and specificity (99%) in detecting residual AVMs. Different MRI sequences, including 3D TOF-MRA, 4D MRA, and arterial spin-labeling (ASL) demonstrated varying diagnostic accuracies with areas under the curve of 0.92, 0.97, and 0.96, respectively. 4D MRA had a sensitivity of 72% and specificity of 99%, ASL showed a sensitivity of 90% and specificity of 92%, while 3D TOF-MRA had 90% sensitivity and 87% specificity. Meta-regression did not fully explain the sources of heterogeneity. Only 1 study assessed the susceptibility-weighted angiography (SWAN) method, and most studies involved small participant groups with varied MR techniques and sequences. Additionally, the retrospective nature of most studies may introduce bias, warranting cautious interpretation of the results. MRI sequences show acceptable diagnostic performance in postradiosurgery monitoring of brain AVMs, with ASL and 4D MRA showing acceptable diagnostic accuracy. Combining different MRI sequences may further enhance diagnostic reliability. However, further investigation is needed to assess whether MRI sequences can serve as a feasible substitute for DSA, considering their risk-benefit profile, with the potential to establish them as the recommended standard.

The hemodynamic and geometric characteristics of carotid artery atherosclerotic plaque formation.

Ischemic stroke, which has a high incidence, disability, and mortality rate, is mainly caused by carotid atherosclerotic plaque. The difference in the geometric structures of the carotid arteries inevitably leads to the variability in the local hemodynamics, which plays a key role in the formation of carotid atherosclerosis. At present, the combined mechanisms of hemodynamic and geometric in the formation of carotid atherosclerotic plaque are not clear. Thus, this study characterized the geometric and hemodynamic characteristics of carotid atherosclerotic plaque formation using four-dimensional (4D) flow magnetic resonance imaging (MRI). Ultimately, 122 carotid arteries from 61 patients were examined in this study. According to the presence of plaques at the bifurcation of the carotid artery on cervical vascular ultrasound (US), carotid arteries were placed into a plaque group (N=69) and nonplaque group (N=53). The ratio of the maximum internal carotid artery (ICA) inner diameter to the maximum common carotid artery (CCA) inner diameter (ICA-CCA diameter ratio), bifurcation angle, and tortuosity were measured using neck three-dimensional time-of-flight magnetic resonance angiography (3D TOF-MRA). Meanwhile, 4D flow MRI was used to obtain the following hemodynamic parameters of the carotid arteries: volume flow rate, velocity, wall shear stress (WSS), and pressure gradient (PG). Independent sample t-tests were used to compare carotid artery geometry and hemodynamic changes between the plaque group and nonplaque group. The ICA-CCA diameter ratio between the plaque group and the nonplaque group was not significantly different (P=0.124), while there were significant differences in the bifurcation angle (P=0.005) and tortuosity (P=0.032). The bifurcation angle of the plaque group was greater than that of the nonplaque group (60.70°±20.75° vs. 49.32°±22.90°), and the tortuosity was smaller than that of the nonplaque group (1.07±0.04 vs. 1.09±0.05). There were no significant differences between the two groups in terms of volume flow rate (P=0.351) and the maximum value of velocity (velocitymax) (P=0.388), but the axial, circumferential, and 3D WSS values were all significantly different, including their mean values (all P values <0.001) and the maximum value of 3D WSS (P<0.001), with the mean axial, circumferential, 3D WSS values, along with the maximum 3D WSS value, being lower in the plaque group. The two groups also differed significantly in terms of maximum PG value (P=0.030) and mean PG value (P=0.026), with these values being greater in the nonplaque group than in the plaque group. A large bifurcation angle and a low tortuosity of the carotid artery are geometric risk factors for plaque formation in this area. Low WSS and low PG values are associated with carotid atherosclerotic plaque formation.

Deep learning-based platform performs high detection sensitivity of intracranial aneurysms in 3D brain TOF-MRA: An external clinical validation study

PurposeTo evaluate the diagnostic efficacy of a developed artificial intelligence (AI) platform incorporating deep learning algorithms for the automated detection of intracranial aneurysms in time-of-flight (TOF) magnetic resonance angiography (MRA). MethodThis retrospective study encompassed 3D TOF MRA images acquired between January 2023 and June 2023, aiming to validate the presence of intracranial aneurysms via our developed AI platform. The manual segmentation results by experienced neuroradiologists served as the “gold standard”. Following annotation of MRA images by neuroradiologists using InferScholar software, the AI platform conducted automatic segmentation of intracranial aneurysms. Various metrics including accuracy (ACC), balanced ACC, area under the curve (AUC), sensitivity (SE), specificity (SP), F1 score, Brier Score, and Net Benefit were utilized to evaluate the generalization of AI platform. Comparison of intracranial aneurysm identification performance was conducted between the AI platform and six radiologists with experience ranging from 3 to 12 years in interpreting MR images. Additionally, a comparative analysis was carried out between radiologists’ detection performance based on independent visual diagnosis and AI-assisted diagnosis. Subgroup analyses were also performed based on the size and location of the aneurysms to explore factors impacting aneurysm detectability. Results510 patients were enrolled including 215 patients (42.16 %) with intracranial aneurysms and 295 patients (57.84 %) without aneurysms. Compared with six radiologists, the AI platform showed competitive discrimination power (AUC, 0.96), acceptable calibration (Brier Score loss, 0.08), and clinical utility (Net Benefit, 86.96 %). The AI platform demonstrated superior performance in detecting aneurysms with an overall SE, SP, ACC, balanced ACC, and F1 score of 91.63 %, 92.20 %, 91.96 %, 91.92 %, and 90.57 % respectively, outperforming the detectability of the two resident radiologists. For subgroup analysis based on aneurysm size and location, we observed that the SE of the AI platform for identifying tiny (diameter＜3mm), small (3 mm ≤ diameter＜5mm), medium (5 mm ≤ diameter＜7mm) and large aneurysms (diameter ≥ 7 mm) was 87.80 %, 93.14 %, 95.45 %, and 100 %, respectively. Furthermore, the SE for detecting aneurysms in the anterior circulation was higher than that in the posterior circulation. Utilizing the AI assistance, six radiologists (i.e., two residents, two attendings and two professors) achieved statistically significant improvements in mean SE (residents: 71.40 % vs. 88.37 %; attendings: 82.79 % vs. 93.26 %; professors: 90.07 % vs. 97.44 %; P < 0.05) and ACC (residents: 85.29 % vs. 94.12 %; attendings: 91.76 % vs. 97.06 %; professors: 95.29 % vs. 98.82 %; P < 0.05) while no statistically significant change was observed in SP. Overall, radiologists’ mean SE increased by 11.40 %, mean SP increased by 1.86 %, and mean ACC increased by 5.88 %, mean balanced ACC promoted by 6.63 %, mean F1 score grew by 7.89 %, and Net Benefit rose by 12.52 %, with a concurrent decrease in mean Brier score declined by 0.06. ConclusionsThe deep learning algorithms implemented in the AI platform effectively detected intracranial aneurysms on TOF-MRA and notably enhanced the diagnostic capabilities of radiologists. This indicates that the AI-based auxiliary diagnosis model can provide dependable and precise prediction to improve the diagnostic capacity of radiologists.

Multimodal MRI segmentation of key structures for microvascular decompression via knowledge-driven mutual distillation and topological constraints.

Microvascular decompression (MVD) is a widely used neurosurgical intervention for the treatment of cranial nerves compression. Segmentation of MVD-related structures, including the brainstem, nerves, arteries, and veins, is critical for preoperative planning and intraoperative decision-making. Automatically segmenting structures related to MVD is still challenging for current methods due to the limited information from a single modality and the complex topology of vessels and nerves. Considering that it is hard to distinguish MVD-related structures, especially for nerve and vessels with similar topology, we design a multimodal segmentation network with a shared encoder-dual decoder structure and propose a clinical knowledge-driven distillation scheme, allowing reliable knowledge transferred from each decoder to the other. Besides, we introduce a class-wise contrastive module to learn the discriminative representations by maximizing the distance among classes across modalities. Then, a projected topological loss based on persistent homology is proposed to constrain topological continuity. We evaluate the performance of our method on in-house dataset consisting of 100 paired HR-T2WI and 3D TOF-MRA volumes. Experiments indicate that our model outperforms the SOTA in DSC by 1.9% for artery, 3.3% for vein and 0.5% for nerve. Visualization results show our method attains improved continuity and less breakage, which is also consistent with intraoperative images. Our method can comprehensively extract the distinct features from multimodal data to segment the MVD-related key structures and preserve the topological continuity, allowing surgeons precisely perceiving the patient-specific target anatomy and substantially reducing the workload of surgeons in the preoperative planning stage. Our resources will be publicly available at https://github.com/JaronTu/Multimodal_MVD_Seg .

ACCURACY OF SUSCEPTIBILITY WEIGHTED IMAGING AND 3D-TOF MRA IN DETECTION AND PRE-TREATMENT EVALUATION OF INTRACRANIAL DURAL ARTERIOVENOUS FISTULAS

Background: Dural arteriovenous fistulas (DAVFs) are abnormal connections between meningeal arteries and dural venous sinuses or cortical veins. A cerebral angiogram is the gold standard for diagnosing and treating DAVFs. Still, non-invasive techniques such as three-dimensional time-offlight magnetic resonance angiography (3D-TOF MRA) and susceptibility-weighted imaging (SWI) are also helpful in evaluating the location and severity of the fistulas, including cortical venous reflux (CVR) and cortical venous ectasia (CVE). This study aimed to compare the efficacy in detecting and pretreating DAVFs evaluating SWI and 3D-TOF MRA with cerebral angiography. Methods: The retrospective study included 35 patients with 41 DAVFs who underwent pre-treatment MR imaging and cerebral angiogram. The fistulous point at convexity and cavernous locations, arterial feeders, venous drainers, CVR, and CVE were evaluated. Results: SWI and 3D-TOF MRA showed high sensitivity and excellent specificity in detecting DAVFs Cognard II-IV at convexity location and high sensitivity in evaluating CVR. For DAVFs at cavernous sinus locations, arterial feeders and venous drainers were significantly identified in 3D-TOF MRA (p &lt; 0.001). SWI exhibited superior sensitivity (87.5%) in detecting CVE at convexity locations (p &lt; 0.001). Slow flow or low-grade fistulas in cavernous sinus locations (n = 2, 4.8%, Cognard I) were not identified using MR imaging. Conclusion: SWI and 3D-TOF MRA are helpful tools for evaluating high-flow DAVFs (Cognard II-IV). SWI is superior in detecting CVE in convexity locations but is limited in assessing the fistulous point in cavernous sinus locations. Thus, combining findings from both SWI and 3D-TOF MRA exhibited high accuracy in detecting and pretreating high-flow DAVFs.

Diagnosis of a Dural Arteriovenous Fistula Involving the Superior Sagittal Sinus: The MMA Sign on Routine 3D-TOF MR Angiography

The main feeding artery of a dural arteriovenous fistula (DAVF) involving the superior sagittal sinus (SSS) is the middle meningeal artery (MMA). MMA extends continuously from the proximal part to SSS in DAVF involving SSS. It is possible to diagnose DAVF involving SSS by evaluating the proximal part of MMA on routine three-dimensional time-of-flight MR angiography (MRA). We termed the finding in an anteroposterior maximum intensity projection (MIP) image of routine MRA in which MMA was continuously visualized at the top of the imaging slab (the upper corpus callosum level) without tapering as the MMA sign. The purpose of the present study was to examine the frequency of the MMA sign on routine MRA in patients with DAVF involving SSS and control patients. Subjects comprised 18 patients with DAVF involving SSS confirmed by angiography and 871 control subjects who underwent routine MRA. The presence of the MMA sign was retrospectively evaluated using an anteroposterior MIP image of routine MRA in patients with DAVF involving SSS and control patients. The MMA sign was observed in 17 of the 18 (94%) patients with DAVF involving SSS. In one patient with DAVF involving the posterior part of SSS without the MMA sign, the main feeding artery was the occipital artery, not MMA. The MMA sign was observed in 13 of the 871 (1.5%) control patients. The MMA sign on routine MRA is useful, suggesting DAVF involving SSS.

Image Diagnosis for Hemifacial Spasm

Cisternography using heavy T2-weighted images from 3-Tesla magnetic resonance imaging(MRI)and three-dimensional time-of-flight MR angiography(3D TOF MRA)is useful for identifying conflicting vessels in primary hemifacial spasm(HFS). Cisternography provides high-signal images of the cerebrospinal fluid and low-signal images of the cranial nerves and cerebral blood vessels, whereas 3D TOF MRA provides high-signal images with only vascular information. The combination of these two methods increases the identification rate of conflicting vessels. The neurovascular conflict(NVC)site in HFS is where the facial nerve exits the brainstem. However, on MRI, the true NVC site is often more proximal than the facial nerve attachment to the brainstem. On preoperative MRI, it is important to not miss the blood vessels surrounding the proximal portion of the facial nerve. If multiple compression vessels or deep vessels are located in the supraolivary fossette, they may be missed. Coronal section imaging and multiplanar reconstruction(MPR)minimize the chances of missing a compression vessel. Preoperative MRI and CT can also provide various other information, such as volume of the cerebellum, presence of emissary veins, shape of the petrosal bone, and size of the flocculus.

Joint two-stage convolutional neural networks for intracranial aneurysms detection on 3D TOF-MRA

Objective. This study aims to develop a three-dimensional convolutional neural network utilizing computer-aided diagnostic technology to facilitate the detection of intracranial aneurysms and automatically assess their location and extent, thereby enhancing the efficiency of radiologists, and streamlining clinical workflows. Approach. A retrospective study was conducted, proposing a joint segmentation and classification network (JSCD-Net) that employs 3D time-of-flight magnetic resonance angiography images for preliminary detection of aneurysms and the minimization of false positives. Specifically, the U-Net++ network was utilized for pre-detection of aneurysms. This was followed by the creation of a multi-path network, co-trained with U-Net++ to correct the results of the first stage to further reduce the rate of false positives. Model effectiveness and robustness were evaluated using sensitivity and false positive analyses on internal and external datasets. A cross-validated free-response receiver operating characteristic curve was also plotted. Main results. JSCD-Net demonstrated a sensitivity of 91.2% (31 of 34; 95% CI: 77.0, 97.0) with an average of 3.55 false positives per scan on the internal test set. For the external test set, it identified 97.2% (70 of 72; 95% CI: 90.4, 99.2) of aneurysms with an average of 2.7 false positives per scan. Significance. When compared with the existing studies, the proposed model shows high sensitivity in detecting intracranial aneurysms with a reasonable number of false positives per case. This result emphasizes the model’s potential as a valuable tool in aiding clinical diagnoses.

Anatomical information of the lenticulostriate arteries on high-resolution 3D-TOF MRA at 3T: comparison with 3D-DSA.

As the lenticulostriate arteries (LSAs) perfuse neurologically important areas, it is necessary to accurately assess the origin and number of the LSAs before surgery. Although three-dimensional time-of-flight MR angiography (3D-TOF MRA) is a non-invasive procedure, it requires high-resolution (HR) images to depict the LSAs with a small diameter. Therefore, we performed 3D-TOF MRA with the maximum HR (HR-MRA) using a 3T scanner to examine whether a good depiction of the LSAs, equivalent to that of digital subtraction angiography (DSA), could be obtained. Our study group comprised 16 consecutive patients who underwent HR-MRA and 3D-DSA. In both studies, we evaluated the localization of the origin from M1, M2, or A1 segments, their number of stems, and depiction. There was no significant difference in the visualization of the LSAs between HR-MRA and 3D-DSA (P values; M1, M2, and A1 = 0.39, 0.69, and 0.69, respectively), and both the number of stems and the localization of the origin of the LSAs corresponded between the two examinations. HR-MRA at 3T can depict the LSA well. It reveals the number of the LSA stems and the LSA origin comparatively with DSA.

Association between morphologic features of intracranial distal arteries and brain atrophy indexes in cerebral small vessel disease: a voxel-based morphometry study.

Brain atrophy represents a final common pathway for pathological processes in patients with cerebral small vessel disease (CSVD) and is now recognized as a strong independent predictor of clinical status and progression. The mechanism underlying brain atrophy in patients with CSVD is not yet fully comprehended. This study aims to investigate the association of morphologic features of intracranial distal arteries (A2, M2, P2 and more distal) with different brain structures [gray matter volume (GMV), white matter volume (WMV), and cerebrospinal fluid volume (CSFV)]. Furthermore, we also examined whether a correlation existed between these cerebrovascular characteristics and GMV in different brain regions. A total of 39 participants were eventually enrolled. The morphologic features of intracranial distal arteries based on TOF-MRA were extracted and quantified using the intracranial artery feature extraction technique (iCafe). The brain 3D-T1 images were segmented into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using the "Segment" tool in CAT12 for the voxel-based morphometry (VBM) analysis. Univariable and multivariable linear regression models were used to investigate the relationship between these cerebrovascular features and different brain structures. Partial correlation analysis with a one-tailed method was used to evaluate the relationship between these cerebrovascular features and GMV in different brain regions. Our findings indicate that both distal artery length and density were positively correlated with GM fraction in CSVD patients, regardless of whether univariable or multivariable linear regression analyses were performed. In addition, distal artery length (β = -0.428, p = 0.007) and density (β = -0.337, p = 0.036) were also found to be negative associated with CSF fraction, although this relationship disappeared after adjusting for potential confounders. Additional adjustment for the effect of WMHs volume did not change these results. In subgroup anasysis, we found that participants in the highest distal artery length tertile had significantly higher GM fraction and lower CSF fraction level than participants in the lowest distal artery length tertile. In partial correlation analysis, we also found that these cerebrovascular characteristics associated with regional GMV, especially subcortical nuclear. The morphologic features of intracranial distal arteries, including artery length, density and average tortuosity, measured from 3D-TOF MRA, are associated with generalized or focal atrophy indexes of CSVD.

3D multimodal image fusion based on MRI in the preoperative evaluation of microvascular decompression: A meta‑analysis.

Neurovascular compression (NVC) is the main cause of hemifacial spasm (HFS) or trigeminal neuralgia (TN), and frequently occurs at the root entry zone of cranial nerves. Microvascular decompression (MVD) is an effective surgical treatment for TN and HFS caused by NVC. The accurate preoperative diagnosis of NVC is crucial to the evaluation of MVD as an appropriate treatment for TN and HFS. Three-dimensional (3D) time-of-flight magnetic resonance angiography (3D TOF MRA) and high resolution T2-weighted imaging (HR T2WI) are used to detect NVC prior to MVD; however, this combination alone has certain disadvantages. Multimodal image fusion (MIF) may combine two or more images from the same or different modalities, allowing neurosurgeons to use the reconstructed 3D model to observe anatomical details more clearly from different perspectives. The aim of the present meta-analysis was to evaluate the effect of 3D MIF based on 3D TOF MRA combined with HR T2WI in the preoperative diagnosis of NVC, and thus to evaluate its clinical application value in the preoperative evaluation of MVD. Relevant studies available on PubMed, Embase, Web of Science, Scopus, China National Knowledge Infrastructure and the Cochrane Library, and published from the inception of each database to September 2022, were retrieved. Studies using 3D MIF based on 3D TOF MRA combined with HR T2WI to diagnose NVC in patients with TN or HFS were included. The Quality Assessment of Diagnostic Accuracy Studies checklist was used to evaluate the quality of the included studies. The statistical software Stata 16.0 was used to perform the meta-analysis. Data extraction was performed by two independent investigators and discrepancies were resolved by discussion. Pooled sensitivities, specificities, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) and the area under the receiver operating characteristic curve (AUROC) were calculated as the main summary effect size. The I² and Q-test were used to assess heterogeneity. The present search identified 702 articles, of which 7 (comprising 390 patients) fulfilled the inclusion criteria. Bivariate analysis indicated that the pooled sensitivity and specificity of 3D MIF based on 3D TOF MRA combined with HR T2WI for detecting NVC were 0.97 (95% CI, 0.95-0.99) and 0.89 (95% CI, 0.77-0.95), respectively. The pooled PLR was 8.8 (95% CI, 4.1-18.6), the pooled NLR was 0.03 (95% CI, 0.02-0.06) and the pooled DOR was 291 (95% CI, 99-853). The AUROC was 0.98 (95% CI, 0.97-0.99). The studies had no substantial heterogeneity (I2=0; Q=0.000; P=0.50). The present results suggested that 3D MIF based on 3D TOF MRA combined with HR T2WI had excellent sensitivity and specificity for diagnosing NVC in patients with TN or HFS. Therefore, this method should serve a key role in MVD preoperative evaluation.

Verifying the Accuracy of Hemodynamic Analysis Using High Spatial Resolution 3D Phase-contrast MR Imaging on a 7T MR System: Comparison with a 3T System.

Hemodynamics is important in the initiation, growth, and rupture of intracranial aneurysms. Since intracranial aneurysms are small, a high-field MR system with high spatial resolution and high SNR is desirable for this hemodynamic analysis. The purpose of this study was to investigate whether the accuracy of MR fluid dynamic (MRFD) results based on 3D phase-contrast MR (3D PC MR, non-electrocardiogram[ECG]-gated 4D Flow MRI) data from a human cerebrovascular phantom and human healthy subjects obtained by a 7T MR system was superior to those by a 3T MR system. 3D PC MR and 3D time of flight MR angiography (3D TOF MRA) imaging were performed on a 3T MR system and a 7T MR system for a human cerebrovascular phantom and 10 healthy human subjects, and MRFD analysis was performed using these data. The MRFD results from each MR system were then compared with the following items based on the computational fluid dynamics (CFD) results: 3D velocity vector field; correlation coefficient (R), angular similarity index (ASI), and magnitude similarity index (MSI) of blood flow velocity vectors. In the MRFD results of 3D velocity vectors of the cerebrovascular phantom, noise-like vectors were observed near the vascular wall on the 3T MR system, but no noise was observed on the 7T MR system, showing results similar to those of CFD. In the MRFD results of the cerebrovascular phantom and healthy subjects, the correlation coefficients R, ASI, and MSI of the 7T MR system were higher than those of the 3T MR system, and ASI and MSI of healthy human subjects were significantly different between the two systems. The accuracy of high spatial resolution MRFD using the 7T MR system exceeded that of the 3T MR system.

Different MRI-based methods for the diagnosis of neurovascular compression in trigeminal neuralgia or hemifacial spasm: A network meta-analysis

BackgroundAccurate preoperative diagnosis of neurovascular compression (NVC) is crucial in the treatment of trigeminal neuralgia (TN) or hemifacial spasm (HFS). At present, there are many magnetic resonance imaging (MRI)-based methods for diagnosing NVC in clinical practice. This network meta-analysis (NMA) aimed to evaluate the diagnostic performance of different MRI-based imaging methods for NVC in patients with TN and HFS. Materials and methodsRelated studies based on a search of PubMed, Embase, Web of Science and the Cochrane Library were retrieved. A two-way analysis of variance model was constructed for the Bayesian NMA to compare the performance of different diagnostic imaging methods. ResultsOur search identified 595 articles, of which 26 studies (including 2085 patients) related to 4 diagnostic imaging methods (3D time-of-flight magnetic resonance angiography (3D TOF MRA), high resolution T2-weighted imaging (HR T2WI), 3D TOF MRA combined with HR T2WI, and 3D multimodal image fusion (MIF) based on 3D TOF MRA combined with HR T2WI) were included in this NMA. The results showed that 3D MIF based on 3D TOF MRA combined with HR T2WI had the highest related sensitivity, the highest superiority index and the largest area under the receiver operating characteristic curve among all the methods. Conclusions3D MIF based on 3D TOF MRA combined with HR T2WI had better diagnostic performance for detecting NVC in patients with TN or HSF than other MRI-based imaging methods. This method can be used as an effective tool for preoperative evaluation of MVD.

Three-dimensional time-of-flight magnetic resonance angiography combined with high resolution T2-weighted imaging in preoperative evaluation of microvascular decompression.

Neurovascular compression (NVC) is the main cause of primary trigeminal neuralgia (TN) and hemifacial spasm (HFS). Microvascular decompression (MVD) is an effective surgical method for the treatment of TN and HFS caused by NVC. The judgement of NVC is a critical step in the preoperative evaluation of MVD, which is related to the effect of MVD treatment. Magnetic resonance imaging (MRI) technology has been used to detect NVC prior to MVD for several years. Among many MRI sequences, three-dimensional time-of-flight magnetic resonance angiography (3D TOF MRA) is the most widely used. However, 3D TOF MRA has some shortcomings in detecting NVC. Therefore, 3D TOF MRA combined with high resolution T2-weighted imaging (HR T2WI) is considered to be a more effective method to detect NVC. To determine the value of 3D TOF MRA combined with HR T2WI in the judgment of NVC, and thus to assess its value in the preoperative evaluation of MVD. Related studies published from inception to September 2022 based on PubMed, Embase, Web of Science, and the Cochrane Library were retrieved. Studies that investigated 3D TOF MRA combined with HR T2WI to judge NVC in patients with TN or HFS were included according to the inclusion criteria. Studies without complete data or not relevant to the research topics were excluded. The Quality Assessment of Diagnostic Accuracy Studies checklist was used to assess the quality of included studies. The publication bias of the included literature was examined by Deeks' test. An exact binomial rendition of the bivariate mixed-effects regression model was used to synthesize data. Data analysis was performed using the MIDAS module of statistical software Stata 16.0. Two independent investigators extracted patient and study characteristics, and discrepancies were resolved by consensus. Individual and pooled sensitivities and specificities were calculated. The I² statistic and Q test were used to test heterogeneity. The study was registered on the website of PROSERO (registration No. CRD42022357158). Our search identified 595 articles, of which 12 (including 855 patients) fulfilled the inclusion criteria. Bivariate analysis showed that the pooled sensitivity and specificity of 3D TOF MRA combined with HR T2WI for detecting NVC were 0.96 [95% confidence interval (CI): 0.92-0.98] and 0.92 (95%CI: 0.74-0.98), respectively. The pooled positive likelihood ratio was 12.4 (95%CI: 3.2-47.8), pooled negative likelihood ratio was 0.04 (95%CI: 0.02-0.09), and pooled diagnostic odds ratio was 283 (95%CI: 50-1620). The area under the receiver operating characteristic curve was 0.98 (95%CI: 0.97-0.99). The studies showed no substantial heterogeneity (I2 = 0, Q = 0.001 P = 0.50). Our results suggest that 3D TOF MRA combined with HR T2WI has excellent sensitivity and specificity for judging NVC in patients with TN or HFS. This method can be used as an effective tool for preoperative evaluation of MVD.

A coarse-to-fine cascade deep learning neural network for segmenting cerebral aneurysms in time-of-flight magnetic resonance angiography.

BackgroundAccurate segmentation of unruptured cerebral aneurysms (UCAs) is essential to treatment planning and rupture risk assessment. Currently, three-dimensional time-of-flight magnetic resonance angiography (3D TOF-MRA) has been the most commonly used method for screening aneurysms due to its noninvasiveness. The methods based on deep learning technologies can assist radiologists in achieving accurate and reliable analysis of the size and shape of aneurysms, which may be helpful in rupture risk prediction models. However, the existing methods did not accomplish accurate segmentation of cerebral aneurysms in 3D TOF-MRA.MethodsThis paper proposed a CCDU-Net for segmenting UCAs of 3D TOF-MRA images. The CCDU-Net was a cascade of a convolutional neural network for coarse segmentation and the proposed DU-Net for fine segmentation. Especially, the dual-channel inputs of DU-Net were composed of the vessel image and its contour image which can augment the vascular morphological information. Furthermore, a newly designed weighted loss function was used in the training process of DU-Net to promote the segmentation performance.ResultsA total of 270 patients with UCAs were enrolled in this study. The images were divided into the training (N = 174), validation (N = 43), and testing (N = 53) cohorts. The CCDU-Net achieved a dice similarity coefficient (DSC) of 0.616 ± 0.167, Hausdorff distance (HD) of 5.686 ± 7.020 mm, and volumetric similarity (VS) of 0.752 ± 0.226 in the testing cohort. Compared with the existing best method, the DSC and VS increased by 18% and 5%, respectively, while the HD decreased by one-tenth.ConclusionsWe proposed a CCDU-Net for segmenting UCAs in 3D TOF-MRA, and the obtained results show that the proposed method outperformed other existing methods.

Diagnostic yield of TOF-MRA for detecting incidental vascular lesions in patients with cognitive impairment: An observational cohort study.

ObjectivesThe role of three-dimensional (3D) TOF-MRA in patients with cognitive impairment is not well established. We evaluated the diagnostic yield of 3D TOF-MRA for detecting incidental extra- or intracranial artery stenosis and intracranial aneurysm in this patient group.MethodsThis retrospective study included patients with cognitive impairment undergoing our brain MRI protocol from January 2013 to February 2020. The diagnostic yield of TOF-MRA for detecting incidental vascular lesions was calculated. Patients with positive TOF-MRA results were reviewed to find whether additional treatment was performed. Logistic regression analysis was conducted to identify the clinical risk factors for positive TOF-MRA findings.ResultsIn total, 1,753 patients (mean age, 70.2 ± 10.6 years; 1,044 women) were included; 199 intracranial aneurysms were detected among 162 patients (9.2%, 162/1,753). A 3D TOF-MRA revealed significant artery stenoses (>50% stenosis) in 162 patients (9.2%, 162/1,753). The overall diagnostic yield of TOF-MRA was 16.8% (294/1,753). Among them, 92 patients (31.3%, 92/294) underwent either medical therapy, endovascular intervention, or surgery. In total, eighty-one patients with stenosis were prescribed with either antiplatelet medications or lipid-lowering agent. In total, fifteen patients (aneurysm: 11 patients, stenosis: 4 patients) were further treated with endovascular intervention or surgery. Thus, the “number needed to scan” was 19 for identifying one patient requiring treatment. Multivariate logistic regression analysis showed that being female (odds ratio [OR] 2.05) and old age (OR 1.04) were the independent risk factors for intracranial aneurysm; being male (OR 1.52), old age (OR 1.06), hypertension (OR 1.78), and ischemic heart disease history (OR 2.65) were the independent risk factors for significant artery stenosis.ConclusionsOur study demonstrated the potential benefit of 3D TOF-MRA, given that it showed high diagnostic yield for detecting vascular lesions in patients with cognitive impairment and the considerable number of these lesions required further treatment. A 3D TOF-MRA may be included in the routine MR protocol for the work-up of this patient population, especially in older patients and patients with vascular risk factors.

Aneurysmal wall enhancement and hemodynamics: pixel-level correlation between spatial distribution.

Inflammation and hemodynamics are interrelated risk factors for intracranial aneurysm rupture. This study aimed to identify the relationship between these risk factors from an individual-patient perspective using biomarkers of aneurysm wall enhancement (AWE) derived from high-resolution magnetic resonance imaging (HR-MRI) and hemodynamic parameters by four-dimensional flow MRI (4D-flow MRI). A total of 29 patients with 29 unruptured intracranial aneurysms larger than 4 mm were included in this prospective cross-sectional study. A total of 24 aneurysms had AWE and 5 did not have AWE. A three-dimensional (3D) vessel model of each individual aneurysm was generated with 3D time-of-flight magnetic resonance angiography (3D TOF-MRA). Quantification of AWE was sampled with HR-MRI. Time-averaged wall shear stress (WSS) and oscillatory shear index (OSI) were calculated from the 4D-flow MRI. The correlation between spatial distribution of AWE and hemodynamic parameters measured at pixel-level was evaluated for each aneurysm. In aneurysms with AWE, the spatial distribution of WSS was negatively correlated with AWE in 100% (24/24) of aneurysms, though 2 had an absolute value of the correlation coefficient <0.1. The OSI was positively correlated with AWE in 91.7% (22/24) of aneurysms; the other 2 aneurysms showed a negative correlation with AWE. In aneurysms with no AWE, there was no correlation between WSS (100%, 5/5), OSI (80%, 4/5), and wall inflammation. The spatial distribution of WSS was negatively correlated with AWE in aneurysms with AWE, and OSI was positively correlated with AWE in most aneurysms with AWE. While aneurysms that did not contain AWE showed no correlation between hemodynamics and wall inflammation.

Multiple hypointense veins on susceptibility weighted imaging as a promising biomarker of impaired cerebral hemodynamics in chronic steno-occlusive disease: a multiparametric MRI study.

Patients with steno-occlusive arterial disease may develop cerebral hypoperfusion with possible neurologic sequelae. The aim of the study is to verify the possible role of SWI, as a marker of cerebral hypoperfusion, in the identification of patient subgroups with significant chronic occlusions/stenoses at risk of critical cerebral hypoperfusion. We retrospectively identified 37 asymptomatic patients with chronic intra-extracranial occlusion/stenosis of the anterior circulation from a prospective brain MRI register between 2016 and 2020. All patients underwent 3 Tesla MRI. The imaging protocol included the following: SWI, 3D-FLAIR, DWI sequences, and 3D-TOF MRA. SWI findings were graded for the presence of asymmetric intracranial cortical veins (grades 1 to 4). The presence of collateralization was assessed with concomitant multiphase-CTA. FLAIR was evaluated for the presence of distal hyperintense vessels (DHVs), a described marker of flow impairment, and possible collateralization. Cerebral blood flow and arterial transit artifacts (ATAs) were evaluated at pCASL in 29 patients. SWI showed multiple hypointense vessels (MHVs) in 22/37 patients in the cerebral hemisphere ipsilateral to vessel occlusion/stenosis. SWI-MHV grade 1 was found in 15 patients (40.5%), grade 2 in 18 patients (48.7%), and grade 3 in 3 patients (8.1%); in one patient, SWI was graded as 4 (2.7%). A significant relationship was found among MHV, DHV, collaterals, ATAs, and hypoperfused areas on pCASL and with patients' previous neurological symptoms. SWI-MVH correlates with chronic cerebral flow impairment and is related to hypoperfusion and collateralization. It may help identify a subgroup of patients benefitting from revascularization.

Dense, deep learning-based intracranial aneurysm detection on TOF MRI using two-stage regularized U-Net

Background and purposeThe prevalence of unruptured intracranial aneurysms in the general population is high and aneurysms are usually asymptomatic. Their diagnosis is often fortuitous on MRI and might be difficult and time consuming for the radiologist. The purpose of this study was to develop a deep learning neural network tool for automated segmentation of intracranial arteries and automated detection of intracranial aneurysms from 3D time-of-flight magnetic resonance angiography (TOF-MRA). Materials and methods3D TOF-MRA with aneurysms were retrospectively extracted. All were confirmed with angiography. The data were divided into two sets: a training set of 24 examinations and a test set of 25 examinations. Manual annotations of intracranial blood vessels and aneurysms were performed by neuroradiologists. A double convolutional neuronal network based on the U-Net architecture with regularization was used to increase performance despite a small amount of training data. The performance was evaluated for the test set. Subgroup analyses according to size and location of aneurysms were performed. ResultsThe average processing time was 15 min. Overall, the sensitivity and the positive predictive value of the proposed algorithm were 78% (21 of 27; 95% CI: 62–94) and 62% (21 of 34; 95%CI: 46–78) respectively, with 0.5 FP/case. Despite gradual improvement in sensitivity regarding aneurysm size, there was no significant difference of sensitivity detection between subgroups of size and location. ConclusionsThis developed tool based on a double CNN with regularization trained with small dataset, enables accurate intracranial arteries segmentation as well as effective aneurysm detection on 3D TOF MRA.